code: def __call__(self, wav, in_sr):
      if self.toolkit == "speechbrain":
          wav = self.audio_norm(torch.from_numpy(wav), in_sr).to(
              self.device
          )
          embeds = (
              self.model.encode_batch(wav).detach().cpu().numpy()[0]
          )
      elif self.toolkit == "rawnet":
          if in_sr != self.tgt_sr:
              wav = librosa.resample(
                  wav, orig_sr=in_sr, target_sr=self.tgt_sr
              )
          embeds = self._rawnet_extract_embd(wav)
      elif self.toolkit == "espnet":
          if in_sr != self.tgt_sr:
              wav = librosa.resample(
                  wav, orig_sr=in_sr, target_sr=self.tgt_sr
              )
          embeds = self._espnet_extract_embd(wav)
      return embeds
  
file_path: espnet/egs2/how2_2000h/sum1/pyscripts/utils/extract_spk_embed.py
imports: import argparse
  import logging
  import os
  import sys
  from pathlib import Path
  import kaldiio
  import librosa
  import numpy
  import torch
  from tqdm.contrib import tqdm
  from espnet2.fileio.sound_scp import SoundScpReader
label_desc: Use image node_id 4 for calling the SpkEmbedExtractor obj's underlying member method code with example usage: obj.__call__(wav, in_sr) and returns: embeds